Learning-Based Autoencoder for Multiple Access and Interference Channels in Space Optical Communications

Elfikky, Abdelrahman; Soltani, Morteza; Rezki, Zouheir

doi:10.1109/lcomm.2023.3312584

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…ML and AI will play a key role in automating network operations and optimizing the user experience. Some of these actions required for broadband high-speed Internet are end-to-end learning frameworks for channel estimation and symbol detection [117], ML for localization and positioning in Internet-based applications [118], improving data speed and quality, interference mitigation in multiple access [119], and prediction and balancing traffic. Service providers can remotely manage networks and troubleshoot problems in real-time with AI-ML.…”

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confidence: 99%

The Past, Present, and Future of the Internet: A Statistical, Technical, and Functional Comparison of Wired/Wireless Fixed/Mobile Internet

Shirvani Moghaddam

2024

Electronics

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This paper examines the quantitative and qualitative situation of the current fixed and mobile Internet and its expected future. It provides a detailed insight into the past, present, and future of the Internet along with the development of technology and the problems that have arisen in accessing and using broadband Internet. First, the number of users and penetration rate of the Internet, the various types of services in different countries, the ranking of countries in terms of the mean and median download and upload Internet data speeds, Internet data volume, and number and location of data centers in the world are presented. The second task introduces and details twelve performance evaluation metrics for broadband Internet access. Third, different wired and wireless Internet technologies are introduced and compared based on data rate, coverage, type of infrastructure, and their advantages and disadvantages. Based on the technical and functional criteria, in the fourth work, two popular wired and wireless Internet platforms, one based on optical fiber and the other based on the 5G cellular network, are compared in the world in general and Australia in particular. Moreover, this paper has a look at Starlink as the latest satellite Internet candidate, especially for rural and remote areas. The fifth task outlines the latest technologies and emerging broadband Internet-based services and applications in the spotlight. Sixthly, it focuses on three problems in the future Internet in the world, namely the digital divide due to the different qualities of available Internet and new Internet-based services and applications of emerging technologies, the impact of the Internet on social interactions, and hacking and insecurity on the Internet. Finally, some solutions to these problems are proposed.

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Section: And Aimentioning

confidence: 99%

The Past, Present, and Future of the Internet: A Statistical, Technical, and Functional Comparison of Wired/Wireless Fixed/Mobile Internet

Shirvani Moghaddam

2024

Electronics

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Deep Learning Based End-to-End Optical Wireless Communication Systems With Autoencoders

Safi,

Tavakkolnia,

Haas

2024

IEEE Commun. Lett.

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The utilization of neural network-based autoencoders (AEs) for the implementation of the physical layer in communication systems has recently emerged as a promising technique for achieving end-to-end optimization of communication links. However, applying conventional AE architecture to intensity modulation/direct detection optical wireless systems is challenging due to positive real-value constraint, eye safety standards, and the limited dynamic range of light sources. To address these issues, in this paper we propose a practical architecture, namely differential AE, that incorporates the concept of differential signaling. This approach allows the transmission of negative encoder output elements. In a shot-noise limited scenario, we evaluate and contrast the performance of differential AE, conventional AE, and a non-AE classical system, showcasing the superior bit-error rate achieved by the differential AE.

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End-to-End Learning Framework for Space Optical Communications in Non-Differentiable Poisson Channel

Elfikky,

Soltani,

Rezki

2024

IEEE Wireless Commun. Lett.

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Learning-Based Autoencoder for Multiple Access and Interference Channels in Space Optical Communications

Cited by 3 publications

References 9 publications

The Past, Present, and Future of the Internet: A Statistical, Technical, and Functional Comparison of Wired/Wireless Fixed/Mobile Internet

The Past, Present, and Future of the Internet: A Statistical, Technical, and Functional Comparison of Wired/Wireless Fixed/Mobile Internet

Deep Learning Based End-to-End Optical Wireless Communication Systems With Autoencoders

End-to-End Learning Framework for Space Optical Communications in Non-Differentiable Poisson Channel

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